code: def test_basic_estimator_preparation_perf_with_ignored_columns():
      dummy = DummyEstimator()
      shape = (5, 100000)
      data_start = time.time()
      names = ["Col_" + str(n) for n in range(shape[1])]
      y = names[len(names) // 2]  # average worst scenario
      ignored = [
          n for i, n in enumerate(names) if i % 2
      ]  # average worst scenario regardless what preparation is doing
      train_fr = h2o.H2OFrame({n: list(range(shape[0])) for n in names})
      data_duration = time.time() - data_start
      print("data preparation/upload took {}s".format(data_duration))
      training_start = time.time()
      dummy.train(
          y=y,
          training_frame=train_fr,
          validation_frame=train_fr,
          ignored_columns=ignored,
      )
      training_duration = time.time() - training_start
      print("training preparation took {}s".format(training_duration))
      assert training_duration < 10
  
file_path: h2o-3/h2o-py/tests/testdir_algos/common/pyunit_train_preparation_perf.py
imports: import sys
  import time
  import h2o
  from h2o.estimators.estimator_base import H2OEstimator
  from tests import pyunit_utils
label_desc: Use image node_id 2 for calling a global function with example usage: test_basic_estimator_preparation_perf_with_ignored_columns() without return types